Contact centers employ agents to interact with called parties for a variety of purposes, such as debt collection, telemarketing, soliciting donations, or providing customer service. For a variety of applications, there may be various state or federal regulations governing how the interaction may occur. In addition, the contact center may have various policies that govern how the agent is to conduct the call. The agent is expected to comply with the appropriate regulations and policies, but in fact, this may be difficult depending on the particular circumstances. This is because the agent may be involved in various campaigns governed by different regulations and policies. The agent may be temporarily distracted during a call and may not recall all the applicable regulations.
For example, depending on the particular circumstances, the agent may be required to ensure that the certain information is provided to the remote party or respond in a certain way when provided with information by the remote party. In the past, one way of ensuring that the agent complied with the applicable regulations or policies was to record the call involving the agent. The call would then be reviewed by an experienced agent who would identify or rank the agent's performance. It is not uncommon for a very small sample of such calls involving an agent to be reviewed, i.e., perhaps a fraction of 1% of the calls. Further, such a review may occur days or weeks after the call was initially recorded. This approach could only identify a deficiency in an agent's performance long after the call was completed. There may have been hundreds of calls made by the agent before any feedback is provided to the agent. Thus, any errors in the agent's call handling practice may go uncorrected for some time.
Agents may have a genuine desire to improve their performance, but they may not be aware that they have made a mistake. They may be distracted, nervous, or simply unaware that they overlooked an opportunity to improve their performance or were non-compliant in a particular circumstance. Real-time feedback is typically more effective in modifying human behavior, and delayed review of the agent's performance may serve to entrench undesirable agent habits.
One technology that can be applied to monitor and identify an agent's non-compliance involves the use of real-time speech analytics. This technology can monitor and “understand” the speech and the context of the speech as it occurs in conversation between the agent and remote party. Unlike speech recognition, the speech is analyzed for a particular conversation relative to a particular framework or context. In other words, in order for the speech analysis to detect a non-compliance condition, there must be first a framework defined to compare the speech against. This may be complicated in that the particular framework to use may depend on various factors, and may not be deduced from the speech itself. For example, an agent providing customer service may respond to a called party by saying “I cannot tell you that.” This may be an appropriate answer if the called party inquires about the agent's email address for personal correspondence, but the same response may not be an appropriate answer if the called party seeks the email address for directing a customer complaint. Thus, analyzing the speech during a call is highly dependent on the context in which the speech occurs. That is merely recognizing a word(s) may not be sufficient.
Once an agent's performance is determined for a call, it may be desirable to quickly review the agent's performance for a number of calls during a time period. In different contexts, this review may occur in different formats. One such format could be visually and another format could be aurally. Further, mechanisms need to be defined to allow easily and quickly switching from one format to another.
Thus, systems and methods required to be defined to effectively and quickly review whether an agent is compliance with various regulations and contact center policies. A flexible approach for providing both visual and aural review methods is needed. It is with respect to these and other considerations that the disclosure herein is presented.